DashAI.back.models.BagOfWordsTextClassificationModel

class BagOfWordsTextClassificationModel(**kwargs)

Text classification meta-model.

The metamodel has two main components:

• Tabular classification model: the underlying model that processes the data and

  provides the prediction.

• Vectorizer: a BagOfWords that vectorizes the text into a sparse matrix to give

  the correct input to the underlying model.

The tabular_model and vectorizer are created in the __init__ method and stored in the model.

To train the tabular_model the vectorizer is fitted and used to transform the train dataset.

To predict with the tabular_model the vectorizer is used to transform the dataset.

__init__(**kwargs) → None

Initialize the BagOfWordsTextClassificationModel.

Parameters:

kwargs (dict) – A dictionary containing the parameters for the model, including: - tabular_classifier: Configuration for the underlying classifier. - ngram_min_n: Minimum n-gram value. - ngram_max_n: Maximum n-gram value.

Methods

__init__(**kwargs)	Initialize the BagOfWordsTextClassificationModel.
fit(x, y)	Fit the estimator.
get_schema()	Generates the component related Json Schema.
get_vectorizer(input_column[, output_column])	Factory that returns a function to transform a text classification dataset into a tabular classification dataset.
load(filename)	Load the model of the specified path.
predict(x)
save(filename)	Save the model in the specified path.
validate_and_transform(raw_data)	It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.

Attributes

COMPATIBLE_COMPONENTS
TYPE